Hair transparency decoding in Asia: From stylists’ perception to in vitro measurement

Abstract Background The concept of hair transparency has been claimed widely in the Japan (and now it is spreading to Asian) hair color market. Despite the general use of this concept, to date, there is no clear and objective description to accurately explain what it is. In this work, we have decoded and gave clarity to the concept of hair transparency via a technical model (validated for both Japan and China markets) composed of measurable parameters of hair property using a single device. Methodology and Results A comprehensive study composed of various tests was used, starting with a qualitative identification of key parameters via in‐depth workshop discussions with over 40 Japanese stylists and a panel of 12 consumers. These identified parameters (luminosity, color visibility, and Shine) were then translated into technically measurable parameters of the hair fiber (Diffused light intensity, ratio of RGB channel intensities of Diffused light, and luster) via a single instrument—Hair SAMBA (a dual‐polarized imaging system). Afterward, 10 carefully selected anchor shades were used as visual stimuli in an online pairwise comparison (PC) study with 100 Japanese stylists to generate quantitative transparency perception data of the swatches. Technical parameters of these swatches were measured by SAMBA and consolidated with the PC output, for the creation and validation of the mathematical model. After, with another PC study (N = 100) in China, with seven shades from Japan study and 6 additional Chinese market shades, the applicability of the model in China market was validated. Conclusion We have clarified and quantified the concept of hair transparency through a consumer centric approach and with objective data. Our findings will enable the development of optimum transparent shades which better suits consumer needs. Lastly, we would like to highlight the beauty of digitalization in the study: The digital evaluation pathways chosen allowed us to collect quantitative consumer data from two countries for the creation of a robust model under the impact of COVID‐19 and would definitely be the way to go for our future consumer evaluation studies.


| INTRODUC TI ON
Since 2018, hair transparency ("Tōmei-kan" 透明感) has become a fashion buzz word in Japan for trending hair color and is making its way to China and other East Asian countries. From physics' point of view, transparency is a material property that characterizes its ability to let light pass through. However, the stylists' and consumers' perception of hair transparency is rather complex. Transparency has been claimed widely in Japan hair color market, and despite the high penetration, to date, there is no clear and objective description to accurately explain what it is. In this work, we aim to decode and give clarity to the Japanese trend of hair transparency, by quantification of Japanese/Chinese stylists' perception with a mathematical model, which paves the way for the development of optimum transparent shades to better fulfill consumer needs.
To achieve this goal, a comprehensive study composed of vari-

| ME THODOLOGY
To decode hair transparency trend, Nihon L'Oréal Consumer & Market Insight (CMI) has conducted two studies, one with 12 consumers who place high importance on "transparent hair color" for ideal hair color and another with 40 top Japanese stylists who are actively communicating on "hair transparency." In both studies, it was found that hair transparency has three dimensions: Color-high luminosity and light throughness (often achieved through bleaching agents) with neutralized undertone (red or orange/yellow undertone, especially after bleach application, ie, removal of undertone for color sheerness), color visibility (high contrast between hair colors with/without bright (sun)light); Appearance (Shine)-healthy with beautiful reflect; and Texture-fluidic movement, soft, and fine hair.
In this paper, to simplify the message, we will attempt to capture the perception of hair transparency with the more straightforward visual parameters: color and Shine (Shine is also linked to surface smoothness 1 ). The texture (tactile) aspect will be covered by a follow-up study separately.
To numerically describe hair transparency, we will first need to identify a device which allows us to simultaneous measure the integration of these parameters. Various studies have been conducted on hair Shine measurements in the past 2-4 and on understanding human perception of hair Shine. 5-7 SAMBA Hair System ® (a dualpolarized imaging system developed by Bossa Nova Technologies, USA) has been established to measure hair luster (Shine, See L BNT Eqn. in Figure 1B) and is an industrial standard device for hair Shine measurement. 8 By using a polarization camera system, after illumination, hair "Shine" (first reflection, no color information), "Chroma" (second reflection inside of hair fiber, with color information), and "Diffused" (scattering inside of hair, with color information) can be measured and represented separately, where the sum of Shine and Chroma profiles gives Specular profile. For each of the three profiles, the intensity profiles of R, G, and B channels are captured by the camera, which contains color information. [8][9][10] Hair Shine and surface smoothness were successfully measured by SAMBA previously. 1,11 In a follow-up study by the same group, 12 the overlapping degrees between "Shine" and "Chroma" were used in combination with luster values, to compute hair color vibrance factor (HCVF). They have found that hair color had an impact on HCVF, and the higher the HCVF value, the more vibrant the hair color looks. A skin translucency study by Matsubara (P&G) 13 has demonstrated that the sensorial perception of skin translucency (glow, fairness, and fine texture) could be translated into numerical descriptions using SAMBA face system ® (which shares largely similar working principles with the SAMBA hair system ® ) by looking at the specular rate profiles in RGB channels individually. In this study, we aim to develop the first mathematical model in the industry, which describes hair transparency objectively, by simultaneously measurements of color and Shine parameters, using SAMBA hair system ® .

| Mathematical description of hair transparency using SAMBA data
Based on our observations and understanding of the established interaction mechanism between hair fiber and incident light, we have defined a new parameter-Hair Transparency Index (HTI) to capture the comprehensive effects of hair Shine and color, to describe consumer/stylist perceived hair transparency as follows: where Luminosity = log diffused L int log(100) All the parameters can be directly obtained from SAMBA hair data file. L BNT is the Shine parameter. diffused R int , diffused G int , diffused B int , and diffused L int represent the integral of R, G, B, and L(overall) channel intensities in the obtained Diffused profile respectively. First part of the equation takes care of the color impact on hair transparency definition-(1) higher luminosity in general gives higher HTI (higher luminosity leads to higher perceived transparency by stylists); (2) in terms of color visibility, when hair base color is dark (eg, Asian hair at a no or low bleach level with high melanin content) (correspondingly in SAMBA, we characterize hair is in the dark group when diffused L int < 100), warmer shades (eg, red and pink) tend to be more visible and perceived to be of higher transparency (ie, in SAMBA, the higher the R (red) channel intensity); and when hair base color is bright (eg, Asian hair at high bleach level with more apparent red/orange undertone) (in SAMBA, diffused L int > 100), the better coverage of the hair orange/red undertone (in SAMBA, the lower the R (red) channel intensity), the higher the perceived transparency. Note that because of this difference on color impact, the comparison of HTI values of swatches in the dark group and bright group will not be applicable in this model. Second part of the equation considers for Shine; the higher the Shine and healthier hair appears (in SAMBA, higher L BNT values), the more transparency perceived. The value 75 at the denominator was used to adjust the weightage of the parameters in determining hair transparency. First, let us focus on how Japan PC study (N = 100 Japanese stylists) results matched with the HTI model. PC score was calculated as for each "win" in the pairwise comparison; the sample gets 1 point. Table 1 summarizes the PC ranking (higher score =higher transparency) generated. Cochran's Q test was performed to obtain statistically significant groups (P < .0001).

| Validation of the technical model with quantitative stylists' perception data in Japan
As mentioned earlier, the comparison of HTI values of dark (diffused L int < 100) and bright groups (diffused L int > 100) is not applicable in this model, and we will discuss the results of dark group and bright group swatches separately. From Table 1, we picked 3 swatches from the dark group based on their PC scores, namely A (high transparency), E (medium transparency), and I (low transparency) and checked the HTI values of them (6 measurement points for each shade condition). As shown in the table, we were able to differentiate them in statistically significant and correct order. Figure 4A displays the relationship between HTI values and the PC scores for dark shades, which are linearly correlated (R 2 = 0.71). We then conducted statistical analysis and found that Pearson correlation coefficient (PCC) = 0.843 between HTI (7 darker shades) and JP PC scores, and the correlation is significant at the 0.05 level (2-tailed).
For the 3 bright shades, while we were able to keep the same statistical results of B/F and B/G, it seemed that there was a discrepancy between the PC results (F = G) and HTI prediction (F < G  (Table A1).

| Validation of the technical model with quantitative stylists' perception data in China
Similar to the validation in Japan, there are three criteria to be met in China study (7 shades same as Japan study and 6 new additional shades from China market): (i) The 7 same shades used in both studies (in Japan and in China) have a similar and highly correlated (statistically significant) ranking results; (ii) HTI values of the swatches measured by SAMBA correlate well with the ranking scores generated by China PC study; and (iii) a physical workshop with stylists (N = 9) to qualitatively demonstrate that the perception of these swatches presented in-person is similar to that shown as digital images.
The visual stimuli used are shown in Figure 5 below, and we can see that there was a good agreement in the ranking of the same shades between Japanese (JP) and Chinese (CN) stylists, and between JP and CN PC scores, Pearson correlation coefficient (PCC) = 0.968.
Correlation is significant at the 0.01 level (2-tailed). Table 2 summarizes the PC ranking (higher score =higher transparency) generated in the study in China. Cochran's Q test was performed to obtain statistically significant groups (P <.0001). Figure 6A   to achieve a wide range of color performance of the anchor shades.

| Paired comparison study with Japanese and Chinese stylists
Japan: 100 stylists with a career more than 7 years who actively communicate on hair transparency were recruited. An online platform for paired comparison study developed by Newtone Technologies was used for the study. The question asked was "A set of pictures will be presented to you in pairs. You will have to choose the picture in which you consider to have more hair transparency by clicking on it." We conduct 3 separate PC studies with 3 different types of standard photographs of the 10 selected hair shades were used as visual stimuli (Natural look, aligned and curved look, and images from ColorShot, as shown in Figure 7A-C, respectively, acquisition protocol of type (a), (b), and (c) images are discussed in the section below). We followed up the PC study with an  Figure 8A-C, respectively).
After the PC study was completed, Cochran's Q test was performed to obtain statistically significant groups (P < .0001) by Newtone Technologies for both Japan and China studies.

| Acquisition of standard images used in the study
Type